The design of supply chain networks has attracted more attention in recent years according to business and environmental factors.in this paper a multi objective supply chain network design model aims to minimize network costs while satisfying the desired service level, is presented. A fuzzy goal programming (FGP) solution approach based on fuzzy membership function concept is developed to minimize costs and amount of investment while obtain maximum service level. Numerical experiments are conducted to test the efficiency of proposed solution method.

The paper reflects the importance of social networks in the organization of social communication processes in public administration. The essence of communication in public administration and its paradigm is determined. The main differences between public administration and object-oriented public administration are shown. The paper also describes the importance of social networks in the conduct of communication processes compared to other communication channels. Research on the use of social networks in public administration is conducted based on the results of research of the Ukrainian Government and users of the Ukrainian social networks. The main trends in the use of social networks in public administration in Ukraine are described. According to the results of the study, the possible directions of social networks development in public administration in the context of preserving democratic values were proposed.

Cutting force and chip reduction coefficient is the important index of machinability as it determines the power consumption and amount of energy invested in machining actions. It is primarily influenced by process parameters like cutting speed, feed and depth of cut. This paper presents the application of Taguchi’s parameter design to optimize the parameters for individual responses. For multi-response optimization, Taguchi’s quality loss function approach is proposed. In the present investigation, optimal values of cutting speed, feed and depth of cut are determined to minimize cutting force and chip reduction coefficient during orthogonal turning. The effectiveness of the proposed methodology is illustrated through an experimental investigation in turning mild steel workpiece using high speed steel tool.

The development of the internet infrastructure has generated a new phenomenon and lead to some changes in business strategies as it allowed two-way communications among consumers and companies. At present, social media play a key role in communicating information to people around the world and clearly play a vital role in increasing interaction and awareness in an important way. At present, awareness of diseases has disappeared with new methods. Social networking sites like Twitter, Snapchat and Facebook may change the roles the meanings of information delivery and play a superior in that scope. This research investigates the main factors of the power of social media activities (customization, and e-WOM) towards in-creasing Saudi’s awareness on using m-healthcare apps. The results indicate that customization had a positive and direct influence on increasing Saudi’s awareness towards using m-healthcare apps (Brand Awareness). e-WOM had a positive and direct influence on increasing Saudi’s awareness toward using m-healthcare apps (brand awareness), confirming that the power of social media activities was an imperative contributor to brand equity (brand awareness).

Technology transfer, from research and technology organizations (RTOs) toward local industries, is considered as one of important and significant strategies for countries & apos; industrial development. In addition to recover the enormous costs of research and development for RTOs, successful technology transfer from RTOs toward local firms forms technological foundations and develops the ability to enhance the competitiveness of firms. Better understanding of factors influencing process of technology transfer helps RTOs and local firms prioritize and manage their resources in an effective and efficient way to maximize the success of technology transfer. This paper aims to identify important effective factors in technology transfer from Iranian RTOs and provides a comprehensive model, which indicate the interactions of these factors. In this regard, first, research background is reviewed and Cummings and Teng’s model (2003) [Cummings, J. L., & Teng, B.-S. (2003). Transferring R & D knowledge: The key factors affecting knowledge transfer success. Journal of Engineering and Technology Management, 20(1-2), 39-68.] was selected as the basic model in this study and it was modified through suggesting new factors identified from literature of inter-organizational knowledge and technology transfer and finally a Delphi method was applied for validation of modified model. Then, research conducted used Interpretive Structural Modeling (ISM) to evaluate the relationship between the factors of final proposed model. Results indicate that there were twelve factors influencing on technology transfer process from Iranian RTOs to local firms and also the intensity of absorption capability in transferee could influence on the intensity of desorption capability in transferor.

The use of saturated two-level designs is very popular, especially in industrial applications where the cost of experiments is too high. Standard classical approaches are not appropriate to analyze data from saturated designs, since we could only get the estimates of the main factor effects and we would not have degrees of freedom to estimate the variance of the error. In this paper, we propose the use of empirical Bayesian procedures to get inferences for data obtained from saturated designs. The proposed methodology is illustrated assuming a simulated data set.

Flow-shop problems, as a typical manufacturing challenge, have become an interesting area of research. The primary concern is that the solution space is huge and, therefore, the set of feasible solutions cannot be enumerated one by one. In this paper, we present an efficient solution strategy based on a genetic algorithm (GA) to minimize the makespan, total waiting time and total tardiness in a flow shop consisting of n jobs and m machines. The primary objective is to minimize the job waiting time before performing the related operations. This is a major concern for some industries such as food and chemical for planning and production scheduling. In these industries, there is a probability of the decay and deterioration of the products prior to accomplishment of operations in workstation, due to the increase in the waiting time. We develop a model for a flowshop scheduling problem, which uses the planner-specified weights for handling a multi-objective optimization problem. These weights represent the priority of planning objectives given by managers. The results of the proposed GA and classic GA are analyzed by the analysis of variance (ANOVA) method and the results are discussed.

Quality of services in banking industry plays essential role in measuring the performance of banks. As customer awareness increases on the services offered by banks, expectations from service quality increases too. Presently, managers of banks use different financial factors such as deposits, credits, etc. to rank their banks. This paper uses SERVQUAL technique to measure customer satisfaction for 14 branches of a bank in city of Kermanshah, Iran. The study first statistically shows that customer satisfaction was not the same for all these banks and then using analytical hierarchy process and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) ranks these branches using five components of SERVQUAL method; namely tangibles, reliability, assurance, responsiveness and empathy.

Selection of industrial robots for the present day’s manufacturing organizations is one of the most difficult assignments due to the presence of a wide range of feasible alternatives. Robot manufacturers are providing advanced features in their products to sustain in the globally competitive environment. For this reason, selection the most suitable robot for a given industrial application now becomes a more complicated task. In this paper, four models of data envelopment analysis (DEA), i.e. Charnes, Cooper and Rhodes (CCR), Banker, Charnes and Cooper (BCC), additive, and cone-ratio models are applied to identify the feasible robots having the optimal performance measures, simultaneously satisfying the organizational objectives with respect to cost and process optimization. Furthermore, the weighted overall efficiency ranking method of multi-attribute decision-making theory is also employed for arriving at the best robot selection decision from the short-listed competent alternatives. In order to demonstrate the relevancy and distinctiveness of the adopted DEA-based approach, two real time industrial robot selection problems are solved.

Flexible manufacturing system (FMS) is an important component of competitive strategy, which could be used for improving organizational performance, productivity, and profitability. The goal of this research is to use DEMATEL approach for finding the intensity of influence of selected criteria. Then, in order to evaluate flexible manufacturing systems, the results of DEMATEL are used in SAW method. A questionnaire was developed and ten professional experts working in various departments of Aluminum Composite Panel Industry are asked to answer its questions. The obtained results reveal that in this case, it is a better choice not to implement and develop FMS.